Licensed assisted access based on low utilization of unlicensed channels

ABSTRACT

A computing device of a telecommunication network can receive crowd-sourced Wi-Fi reports submitted by user equipment based on scans for beacon signals broadcast by Wi-Fi access points. From the crowd-sourced Wi-Fi reports, the computing device can determine when Licensed Assisted Access (LAA) transmissions over channels of an unlicensed spectrum are safe and are not expected to interfere with Wi-Fi transmissions.

RELATED APPLICATIONS

This U.S. patent application claims priority to provisional U.S. PatentApplication No. 62/650,994, entitled “MEASURING UNLICENSED 5 GHZ BANDUTILIZATION TO ESTIMATE GAIN FROM LAA (LICENSED ASSISTED ACCESS) BYANALYZING CROWD SOURCED WIFI BEACON SIGNALS WITH LOCATION INFORMATION,”filed on Mar. 30, 2018, the entirety of which is incorporated herein byreference.

BACKGROUND

User equipment (UE) and base stations of a telecommunication networkprimarily communicate with each other wirelessly using frequencies in alicensed spectrum. For example, UEs and base stations can exchangeLong-Term Evolution (LTE) transmissions over frequencies in a band thathas been licensed by an operator of a telecommunication network for LTEtransmissions.

However, in some cases UEs and base stations can also exchange data overfrequencies in an unlicensed spectrum. For example, Licensed AssistedAccess (LAA) technology can be used to send LTE transmissions overfrequencies in the unlicensed spectrum that are often used for Wi-Fitransmissions. When UEs and base stations send LTE transmissions overboth licensed and unlicensed frequencies, bandwidth can be increasedrelative to sending data over the licensed frequencies alone.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is set forth with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different figures indicates similaror identical items or features.

FIG. 1 depicts an example environment in which user equipment (UE) canconnect to base stations of a telecommunication network over channels ina licensed spectrum as well as channels of an unlicensed spectrum thatmay also be used for Wi-Fi transmissions.

FIG. 2 depicts a UE collecting data from beacon signals broadcasted byWi-Fi access points and submitting a Wi-Fi report to a server.

FIG. 3 depicts an example of aggregated Wi-Fi data that a server cangenerate by compiling individual crowd-sourced Wi-Fi reports receivedfrom UEs.

FIG. 4 depicts an example chart generated by a server from sample Wi-Fireports that shows a number of unique Wi-Fi access points per channel offour 5 GHz bands with respect to a single map tile.

FIGS. 5A and 5B depict example heat maps that indicate how many channelsare free in one or more bands of the unlicensed spectrum.

FIG. 6 depicts two example charts showing a percentage of map tilesspanning New York County that had, in sample data, each possible numberof channels occupied in different combinations of bands.

FIG. 7 depicts channel and channel utilization values being determinedfrom records of aggregated Wi-Fi data.

FIG. 8 depicts average channel utilization values for individualchannels with respect to a map tile.

FIG. 9 depicts an example chart of average channel utilization valuesacross a set of map tiles covering a geographical area with respect tomultiple candidate channels for LAA transmissions.

FIG. 10 depicts an example chart that indicates a total square mileageof aggregated map tiles that, in example data, each share the sameaverage channel utilization value for a channel.

FIG. 11 depicts an example of carrier aggregation probabilitycalculations.

FIG. 12 depicts an example chart that indicates a total area ofaggregated map tiles that, in example data, each share the sameprobability of having a set of three channels free in a particular band.

FIG. 13 depicts example charts indicating a total area of aggregated maptiles that, in example data, each share the same probability of havingthree or more channels free in different bands.

FIG. 14 shows an example of a server's analysis of records from maptiles covering the same location at various times of day.

FIG. 15 depicts an example system architecture for a UE.

FIG. 16 depicts an example system architecture of a server.

FIG. 17 depicts a flow chart of a first method for identifying LAA-safechannels in one or more bands of the unlicensed spectrum.

FIG. 18 depicts a flow chart of a second method for identifying LAA-safechannels in one or more bands of the unlicensed spectrum.

FIG. 19 depicts a flow chart of a method for identifying LAA-safe bandsof channels in the unlicensed spectrum in which at least a predeterminednumber of consecutive channels are expected to be free for carrieraggregation (CA) during LAA transmissions.

DETAILED DESCRIPTION Introduction

In a wireless telecommunication network, user equipment (UE) and networkequipment primarily communicate with each other wirelessly usingfrequencies within one or more spectrums that have been licensed by anoperator of the wireless telecommunication network. However, in somecases communications between UEs and network equipment can also, oralternately, exchange data using unlicensed frequencies, such asfrequencies often used for Wi-Fi communications.

For example, although communications in a Long-Term Evolution (LTE)network may use frequencies in specific bands that have been licensed byan operator of the LTE network for LTE transmissions, Licensed AssistedAccess (LAA) technology can also be used to send LTE transmissions overfrequencies in an unlicensed spectrum. In some examples, carrieraggregation (CA) can be used to send data over both licensed frequenciesand unlicensed frequencies using LAA, thereby increasing bandwidthrelative to sending data over licensed frequencies alone. The increasein bandwidth due to LAA transmissions in the unlicensed spectrum inaddition to regular LTE transmissions in the licensed spectrum can bereferred to as the gain due to LAA.

However, LAA transmissions can potentially interfere with Wi-Fitransmissions when both types of transmissions use the same channels inthe unlicensed spectrum. Wi-Fi transmissions generally use channels in a2.4 GHz band of frequencies in the unlicensed spectrum and/or channelsin a 5 GHz band of frequencies in the unlicensed spectrum. The 2.4 GHzband is often used more heavily for Wi-Fi transmissions than the 5 GHzband because the 2.4 GHz band can provide a wider coverage area and issupported by more legacy devices, although in many cases the 5 GHz bandcan provide higher data transfer speeds.

Channels in the 5 GHz band are generally considered as candidates forLAA transmissions to avoid the risk of interference with channels in themore heavily used 2.4 GHz band. Federal Communications Commission (FCC)rules may also prohibit using 2.4 GHz channels for LAA transmissions.However, even though the 5 GHz band may be used less heavily on averageand 5 GHz channels may be the only candidates for LAA transmissions,there remains a risk of LAA transmissions in the 5 GHz band interferingwith Wi-Fi transmissions in the 5 GHz band. Accordingly, operators ofwireless telecommunication networks have often avoided enabling LAA ordeploying LAA-capable hardware due to concerns about LAA transmissionsinterfering with Wi-Fi transmissions.

Described herein are systems and methods that can use crowd-sourced datato identify geographical areas where utilization of one or more channelsin the unlicensed spectrum is low enough that it is unlikely that LAAtransmissions over those channels in those geographical areas wouldinterfere with Wi-Fi transmissions. Accordingly, network operators canenable LAA transmissions using one or more channels of the unlicensedspectrum within the identified geographical areas to increase bandwidthduring LTE communications, for instance by deploying LAA-compatiblenetwork hardware in the identified geographical areas or by permittingexisting LAA-compatible network hardware and/or UEs to use LAA overchannels of the unlicensed spectrum within the identified geographicalareas.

Example Environments

FIG. 1 depicts an example environment in which user equipment (UE) 102can connect to base stations 104 of a telecommunication network 106 inorder to make or receive calls, transmit or receive messages and/orother data, and/or perform any other network operation. A UE 102 can bea mobile phone such as a smart phone or other cellular phone, a personaldigital assistant (PDA), a personal computer (PC) such as a laptop,desktop, or workstation, a media player, a tablet, a gaming device, asmart watch, a hotspot, or any other type of computing or communicationdevice. Example architecture for a UE 102 is illustrated in greaterdetail in FIG. 15, and is described in detail below with reference tothat figure.

A UE 102 can wirelessly connect to a base station 104. The base station104 can be an evolved Node B (eNB) or other type of access point that islinked to a core network of the telecommunication network 106. The corenetwork can also be connected to other networks, such as an IPMultimedia Subsystem (IMS) and/or the Internet. UEs 102, base stations104, and/or other elements of the telecommunication network 106 can becompatible with one or more wireless access technologies or protocols,such as fifth generation (5G) technologies, Long Term Evolution(LTE)/LTE Advanced technology, High-Speed Data Packet Access(HSDPA)/Evolved High-Speed Packet Access (HSPA+) technology, UniversalMobile Telecommunications System (UMTS) technology, Code DivisionMultiple Access (CDMA) technology, Global System for MobileCommunications (GSM) technology, and/or any other previous or futuregeneration of wireless access technology.

For example, the telecommunication network 106 can be, or include, anLTE network. A core network of an LTE network can be referred to as anEvolved Packet Core (EPC), and an LTE base station 104 can be an eNB.Multiple eNBs can be part of a radio access network known as an EvolvedUniversal Mobile Telecommunications System (UMTS) Terrestrial RadioAccess Network (E-UTRAN), through which UEs 102 can access the EPC ofthe LTE network.

Transmissions between a UE 102 and a base station 104 can occurwirelessly over channels in a licensed spectrum 108 of frequencies. Forexample, an operator of the telecommunication network 106 may havelicensed one or more specific bands of frequencies to be used asdedicated frequencies for LTE transmissions between UEs 102 and basestations 104. Often, frequencies for LTE communications includefrequencies within licensed bands in a range from 600 MHz to 2600 MHz,or other licensed bands. However, Licensed Assisted Access (LAA) canalso allow LTE transmissions between a UE 102 and a base station 104 toat least partially occur over channels in an unlicensed spectrum 110 offrequencies that have not been licensed by entities.

In some examples, carrier aggregation (CA) techniques can be used tosend LTE transmissions between a UE 102 and a base station 104 overmultiple channels at different frequencies to increase the totalbandwidth. While CA can be used to send LTE transmissions over multiplechannels within the licensed spectrum 108, CA can also be used to sendLTE transmissions over one or more channels in the licensed spectrum 108as well as one or more channels in the unlicensed spectrum 110 usingLAA. Accordingly, using LAA to transmit data between a UE 102 and a basestation 104 over frequencies in the unlicensed spectrum 110 cansupplement LTE transmissions in the licensed spectrum 108, therebyincreasing the total available bandwidth and improving data transferspeeds.

Frequencies in the unlicensed spectrum 110 include frequencies oftenused for Wi-Fi transmissions between Wi-Fi access points 112 and UEs 102or other types of computing devices 114. Other computing devices 114 caninclude computers, tablets, gaming consoles, smart devices, and/or otherequipment that may be configured to wirelessly transmit data via Wi-Fibut that may or may not be configured to connect to base stations 104 ofthe telecommunication network 106. Various Wi-Fi standards use channelsin a 2.4 GHz band and/or a 5 GHz band of the unlicensed spectrum 110.For example, Wi-Fi transmissions using 802.11b, 802.11g, and 802.11nstandards can use channels in the 2.4 GHz band, while Wi-Fitransmissions using 802.11a, 802.11ac, and 802.11n standards can usechannels in the 5 GHz band.

Because LAA transmissions and Wi-Fi transmissions can use the same orsimilar frequencies in the unlicensed spectrum 110, in some cases LAAtransmissions between a UE 102 and a base station 104 may causeinterference 116 with Wi-Fi transmissions between Wi-Fi access points112 and UEs 102 or other computing devices 114, as shown in FIG. 1.Although the 2.4 GHz band and/or the 5 GHz band can be used for Wi-Fitransmissions depending on the Wi-Fi standards being used, the 2.4 GHzband is often more crowded. Accordingly, due to FCC rules and/or tolower the risk of interference 116 between LAA transmissions and Wi-Fitransmissions in the heavily used 2.4 GHz band, LAA transmissions oftenuse channels in the 5 GHz band of the unlicensed spectrum 110.

In some examples, certain channels within four Unlicensed NationalInformation Infrastructure (U-NII) bands within the 5 GHz band of theunlicensed spectrum 110 can be considered as candidates for potentiallycarrying LAA transmissions. These include channels in the U-NII-1 band(channels 36, 40, 44, and 48, centered at frequencies ranging from 5180MHz to 5240 MHz), channels in the U-NII-2A band (channels 52, 56, 60,and 64, centered at frequencies ranging from 5260 MHz to 5320 MHz),channels in the U-NII-2C band (channels 100, 104, 108, 112, 116, 120,124, 128, 132, 136, 140, and 144, centered at frequencies ranging from5500 MHz to 5720 MHz), and channels in the U-NII-3 band (channels 149,153, 157, 161, and 165, centered at frequencies ranging from 5745 MHz to5825 MHz). Each individual channel in the U-NII bands can have a 20 MHzbandwidth, such that in this example the 25 candidate channels in theU-NII-1, U-NII-2A, U-NII-2C, and U-NII-3 bands have a total bandwidth of500 MHz.

Although the 5 GHz band may often be less crowded than the 2.4 GHz band,the risk of interference 116 between LAA transmissions and Wi-Fitransmissions in the 5 GHz band of the unlicensed spectrum 110 canremain a concern, especially in geographical areas where use of the 5GHz band for Wi-Fi transmissions is heavier than average. However, aswill be described further below, the telecommunication network 106 caninstruct multiple UEs 102 to report information about Wi-Fi signals theyhave detected to a server 118 or other computing device associated withthe telecommunication network 106. Example architecture for the server118 is illustrated in greater detail in FIG. 16, and is described indetail below with reference to that figure.

FIG. 2 depicts a UE 102 collecting data from beacon signals 202broadcasted by Wi-Fi access points 112 and submitting a Wi-Fi report 204to a server 118 or other computing device associated with atelecommunication network 106. A server 118 can receive numerous Wi-Fireports 204 from UEs 102, and the server 118 can use this crowd-sourceddata to identify when and where the likelihood of interference 116between LAA transmissions and Wi-Fi transmissions over one or morechannels in the 5 GHz band is low enough that 5 GHz channels can beconsidered LAA-safe. Accordingly, the server's analysis of crowd-sourcedWi-Fi reports 204 can estimate the gain LAA transmissions could provideand/or allow the operator of the telecommunication network 106 to deployLAA-capable hardware in geographical areas where channels are determinedto be LAA-safe. Deployed LAA-capable base stations 104 can thenperiodically monitor utilization of unlicensed channels, and useselected channels found to have low utilizations for LAA transmissions.Available bandwidth and/or data transfer speeds between UEs 102 and basestations 104 can therefore be improved when LAA-safe channels can beidentified that have a low risk of interference 116 with Wi-Fitransmissions and LAA-capable hardware can be deployed in response.

A Wi-Fi access point 112 can be a Wi-Fi router or other access point.The Wi-Fi access point 112 can operate a Wi-Fi network that is availableto UEs 102 and other computing devices 114 over a channel of theunlicensed spectrum 110. In some cases, a Wi-Fi access point 112 mayoffer multiple Wi-Fi networks, such as a first Wi-Fi network that uses achannel in the 2.4 GHz band and a second Wi-Fi network that uses achannel in the 5 GHz band such that devices can connect to either Wi-Finetwork using the 2.4 GHz channel or the 5 GHz channel.

A Wi-Fi access point 112 can broadcast a beacon signal 202 that includesinformation about a Wi-Fi network provided by the Wi-Fi access point112. For example, for a particular Wi-Fi network that uses a channel inthe 5 GHz band, the Wi-Fi access point 112 can broadcast a beacon signal202 over frequencies associated with that 5 GHz channel. UEs 102 andother computing devices 114 can be configured to scan throughfrequencies looking for beacon signals 202 so that they can identifyWi-Fi networks that are available at their current location,automatically connect to known Wi-Fi networks, and/or display options tousers about available Wi-Fi networks.

A beacon signal 202 can be a frame that includes multiple types of data,including a Basic Service Set Identifier (BSSID) 206, a Service SetIdentifier (SSID) 208, a Basic Service Set (BSS) Load 210 element,and/or other information about a Wi-Fi network provided by the Wi-Fiaccess point 112. The BSSID 206 can be an identifier for the Wi-Fiaccess point 112, such as a media access control (MAC) address. An SSID208 can also be identifier associated with the Wi-Fi access point 112,such as a text string that can be used as a name for the Wi-Fi networkoperated by the Wi-Fi access point 112.

A BSS Load 210 element in a beacon signal 202 can include informationabout the Wi-Fi access point's current load, such a station countidentifying how many devices are connected to the Wi-Fi access point112, a channel utilization value identifying a percentage of time thatthe Wi-Fi access point 112 sensed that the medium for its channel wasbusy, and an available admission capacity indicating a remaining amountof medium time available via explicit admission control. In someexamples, the BSS Load 210 can be expressed in five bytes of a BSSLOADelement or a Quality of Service BSS (QBSS) Load element of a beaconsignal 202, for instance as used in 802.11e standards. In theseexamples, within these five bytes of the BSS Load 210 element, the firstand second bytes can be the station count value, the third byte can bethe channel utilization value, and the fourth and fifth bytes can be theavailable admission capacity value. Accordingly, in these examples themiddle byte of these five bytes of the BSS Load 210 element can be thechannel utilization value. In other examples, a beacon signal 202 mayexpress a channel utilization value in one or more other bytes of a BSSLoad 210 element, or in another format or field apart from a BSS Load210 element.

The server 118, or another element of the telecommunication network 106,can cause UEs 102 to scan for beacon signals 202 from Wi-Fi accesspoints 112 at regular or varying intervals, log information aboutavailable Wi-Fi networks discovered by the UEs 102, and submit thelogged information to the server 118 in Wi-Fi reports 204. A Wi-Fireport 204 from a UE 102 can include one or more records 212.

Each record 212 in a Wi-Fi report 204 can correspond to an individualWi-Fi network discovered by the UE 102 based on a beacon signal 202received by the UE 102 during a scan. A record 212 about a particularWi-Fi network can contain information extracted from the beacon signal202 for that Wi-Fi network, including its BSSID 206, SSID 208, and/orBSS Load 210. The record 212 can also include other informationdetermined by the UE 102 about the Wi-Fi network, including a channelfrequency 214 and geolocation data 216. The channel frequency 214 canindicate a frequency of a channel used by the Wi-Fi network, such as afrequency at which the beacon signal 202 was found during the UE's scan.The geolocation data 216 can indicate coordinates of the UE 102 when itreceived the beacon signal 202. The geolocation data 216 can bedetermined by Global Positioning System (GPS) functionality of the UE102, cell tower triangulation, Wi-Fi crowdsourcing, or by any othergeolocation technique. In some examples, the geolocation data 216 canalso include an indicator of how precise the coordinates are estimatedto be. A record 212 may also include any other type of information abouta Wi-Fi network, including a timestamp at which a beacon signal 202 wasreceived, a received signal strength value associated with the Wi-Finetwork, and/or any other data about the Wi-Fi network derived from thebeacon signal 202 and/or determined by the UE 102.

In some examples, the telecommunication network 106 can provide UEs 102with a Wi-Fi scanning application that runs on the UE 102 toautomatically scan for beacon signals 202 and submit Wi-Fi reports 204as described above. For example, the telecommunication network 106 canuse over-the-air updates or other distribution methods to provide UEs102 with a Wi-Fi scanning application that runs automatically in thebackground on the UEs 102 to scan for beacon signals 202 and submit theWi-Fi reports 204. In other examples, the telecommunication network 106can provide firmware or operating system updates to UEs 102 that causethe UEs 102 to scan for beacon signals 202 and submit Wi-Fi reports 204,or otherwise send instructions to UEs 102 that cause existing hardwareand/or software components of the UEs 102 to scan for beacon signals 202and submit Wi-Fi reports 204.

In some examples, the telecommunication network 106 can cause UEs 102 toscan for beacon signals 202 at designated intervals, such as once anhour. The telecommunication network 106 can also cause UEs 102 to submitWi-Fi reports 204 at the same or different designated intervals, and/oron demand. For example, a telecommunication network 106 can instruct UEs102 to, once an hour, perform a scan for beacon signals 202 and submit aWi-Fi report 204 that contains records 212 for all Wi-Fi networks foundduring that scan. As another example, a telecommunication network 106can instruct UEs 102 to scan for beacon signals 202 once an hour, butsubmit a Wi-Fi report 204 once a day that contains records 212 for allWi-Fi networks found during multiple scans performed throughout thatday.

In some examples, the telecommunication network 106 can instruct UEs 102to only scan for beacon signals 202 and/or send Wi-Fi reports 204 whenthe UEs 102 are in an active state and are not asleep or in apower-saving idle mode. Accordingly, battery life of the UEs 102 can beconserved by not waking UEs 102 specifically to scan for beacon signals202 or to send Wi-Fi reports 204. Additionally, because UEs 102 aregenerally configured to already scan for beacon signals 202 to findavailable Wi-Fi networks while the UEs 102 are active, scanning forbeacon signals 202 in order to log Wi-Fi data and compile Wi-Fi reports204 as described herein may have a minimal impact on battery life of theUEs 102.

The server 118 can receive crowd-sourced Wi-Fi reports 204 when thetelecommunication network 106 causes large numbers of UEs 102 toindividually scan for beacon signals 202 and submit Wi-Fi reports 204.For example, a telecommunication network 106 can provide a Wi-Fiscanning application to some or all of the UEs 102 associated withsubscribers to its services, such that thousands or even millions of UEs102 can submit Wi-Fi reports 204 to the server 118. Although an operatorof a telecommunication network 106 can also hire individuals to performconventional “drive tests” in which they drive or walk around areas withUEs 102 to scan for beacon signals 202 and collect Wi-Fi data,crowd-sourcing the collection of Wi-Fi reports 204 as described abovecan provide the server 118 with Wi-Fi data associated with largegeographical areas very quickly. For example, in some configurations twomillion UEs 102 can submit Wi-Fi reports 204 that in the aggregatecontain 450 million individual records 212 in a single day. As anotherexample, in a single day 40,000 UEs 102 in New York County can submitWi-Fi reports 204 that in the aggregate contain nine million individualrecords 212 having geolocation data 216 for locations spread acrosssubstantially the entirety of New York County.

FIG. 3 depicts an example of aggregated Wi-Fi data 302 that the server118 can generate by compiling individual crowd-sourced Wi-Fi reports 204received from UEs 102. In some examples, the server 118 can generateaggregated Wi-Fi data 302 based on a set of Wi-Fi reports 204 that arereceived over a period of time from multiple UEs 102, such as bycombining Wi-Fi reports 204 received over a period of five days or anyother period of time. In some examples, geolocation data 216,timestamps, or other data in submitted Wi-Fi reports 204 can be used tofilter or search for records 212 corresponding to desired criteria sothat aggregated Wi-Fi data 302 can be generated that contain records 212specific to the desired criteria. In other examples, master aggregatedWi-Fi data 302 can be generated from submitted Wi-Fi reports 204, andthe master aggregated Wi-Fi data 302 can later be filtered or searchedto find records 212 that have desired criteria. For example, the server118 can generate a set of aggregated Wi-Fi data 302 that containsrecords 212 for a desired geographical area, such as within a particularcounty, city, or neighborhood, or search a previously generated masteraggregated Wi-Fi data 302 for records 212 corresponding to that desiredgeographical area.

As shown in FIG. 3, in some examples the server 118 can also usegeolocation data 216 to plot the positions of individual records 212from aggregated Wi-Fi data 302 on a map 304. The map 304 can be dividedinto a plurality of map tiles 306, such that individual records 212 fromaggregated Wi-Fi data 302 can be plotted within corresponding map tiles306. In some embodiments, the map tiles 306 can correspond to 100 meterby 100 meter areas of the map 304, although in other embodiments the maptiles 306 can have any other dimensions. While FIG. 3 shows records 212plotted onto a map 304 and to individual map tiles 306, in some examplesthe server 118 may identify a set of records 212 that have geolocationdata 216 within one or more specific map tiles 306 without visuallyplotting them on a map 304.

After compiling aggregated Wi-Fi data 302 based on crowd-sourced Wi-Fireports 204, the server 118 can analyze the aggregated Wi-Fi data 302for a particular geographical area so that it can be determined whetherLAA transmissions should be permitted in that particular geographicalarea, and if so on what channels and/or how much bandwidth gain could beprovided by LAA transmissions. In some examples, these determinationscan be made based on identifying channels in the 5 GHz band of theunlicensed spectrum 110 that are not being used by Wi-Fi access points112 in the geographical area, as discussed below with respect to FIGS.4-6. In other examples, these determinations can be made based onidentifying channels in the 5 GHz band of the unlicensed spectrum 110that are being used by Wi-Fi access points 112 in the geographical areabut have utilization levels that are lower than a threshold value, asdiscussed below with respect to FIGS. 7-14.

FIGS. 4-6 depict charts and maps that can be created by a server 118 tohelp determine whether channels in the 5 GHz band of the unlicensedspectrum 110 are not being used by Wi-Fi access points 112 in ageographical area. To determine if any channels in the 5 GHz band of theunlicensed spectrum 110 are not being used by Wi-Fi access points 112 ina particular geographical area, the server 118 can first identify a setof records 212 from aggregated Wi-Fi data 302 that have geolocation data216 corresponding to positions within map tiles 306 that cover thegeographical area.

Within records 212 associated with the same map tile 306, there may benumerous records 212 about a single Wi-Fi access point 112. For example,multiple UEs 102 may have received beacon signals 202 from the sameWi-Fi access point 112 and included data about that Wi-Fi access point112 in their Wi-Fi reports 204. As another example, a single UE 102 mayhave included multiple records 212 about the same Wi-Fi access point 112in its Wi-Fi reports 204, for instance if the UE 102 did not movebetween hourly scans for beacon signals 202. However, from numerousrecords 212 corresponding to an individual map tile 306 in thegeographical area, the server 118 can identify unique Wi-Fi accesspoints 112 based on BSSIDs 206, SSIDs 208, and/or other data. The server118 can also identify channels used by those unique Wi-Fi access points112 by finding channels that map to the channel frequencies 214 used bythe Wi-Fi access points 112 as reported in the records 212. For example,a record 212 in the aggregated Wi-Fi report 302 indicating that a UE 102received a particular beacon signal 202 from a particular Wi-Fi accesspoint 112 at a channel frequency 214 of 5220 MHz can indicate that thatthe particular Wi-Fi access point 112 was using channel 44 (centered at5220 MHz).

After identifying unique Wi-Fi access points 112 in a map tile 306 andthe channels used by those unique Wi-Fi access points 112, the server118 can count the number of unique Wi-Fi access points 112 that use eachchannel of the unlicensed spectrum 110. In some examples, these countsof unique Wi-Fi access points 112 per channel can be illustrated on achart. For example, FIG. 4 depicts a chart generated by the server 118from sample Wi-Fi reports 204 that shows a number of unique Wi-Fi accesspoints 112 per channel of four 5 GHz U-NII bands with respect to aparticular map tile 306. In the example of FIG. 4, the records 212 for aparticular map tile 306 may indicate that all of the channels in theU-NII-1, U-NII-2A, and U-NII-3 bands are being used by at least oneWi-Fi access point 112 within the map tile 306, but only 50% of thechannels in the U-NII-2C band are being used by any Wi-Fi access points112 in the map tile 306. Accordingly, the example chart of FIG. 4 showsthat six of the twelve channels in the U-NII-2C band are free.

Although FIG. 4 depicts an example in which the server 118 counts thenumber of unique Wi-Fi access points 112 per channel using recordscorresponding to a single map tile 306, the server 118 can repeat thisprocess for multiple map tiles 306 in a certain geographical area andfind the number of unique Wi-Fi access points 112 per channel withrespect to each map tile 306. From these counts, the server 118 can alsoidentify how many channels are free (i.e., not being used by any Wi-Fiaccess points 112) in each band.

As shown in the examples of FIGS. 5A and 5B, after using records 212 inaggregated Wi-Fi data 302 to identify how many channels are free in oneor more bands within multiple map tiles 306 across a geographical area,the server 118 can generate heat maps 500 that indicate how manychannels are free in those bands. Individual map tiles 306 can becolored, shaded, or otherwise marked in the heat maps 500 to express thenumber of channels that are free (i.e., not being used by any Wi-Fiaccess points 112) in one or more bands of the unlicensed spectrum 110.Alternately, or in addition, heat maps 500 can indicate a frequencyvalues that correspond to the number of free channels in map tiles 306.For example, instead of indicating that a particular map tile 306 hastwo channels free in the U-MI-1 band, the heat map 500 could also, or inaddition, indicate that the particular map tile 306 has a total of 40MHz free in the U-NII-1 band, corresponding to a combination of the two20 MHz frequency ranges used by each of the two free channels.

As an example, FIG. 5A shows heat maps 500 for each of four 5 GHz U-NIIbands. In the example of FIG. 5A, the shading indicates that althoughmany of the illustrated map tiles 306 in the pictured geographical areahave few or no channels free in the U-NII-1 and U-NII-3 bands, more maptiles 306 have at least some channels free in the U-NII-2A band and allof the map tiles 306 have channels free in the U-NII-2C band. Heat maps500 for multiple bands can also be combined as shown in the example ofFIG. 5B, which indicates that although some map tiles 306 have no freechannels in a combination of the U-NII-1 and U-NII-3 bands (nine totalchannels with an aggregate bandwidth of 180 MHz), all of the map tiles306 have five or more free channels in a combination of the U-NII-2A andU-NII-2C bands (sixteen total channels with an aggregate bandwidth of320 MHz).

Instead of, or in addition to, generating heat maps 500, the server 118can also determine percentages of the total map tiles 306 in ageographical area that have distinct numbers of occupied channels withinone or more bands. For example, FIG. 6 depicts two charts generated fromsample aggregated Wi-Fi data 302 for New York County. The charts show apercentage of map tiles 306 spanning New York County that had, in thesample data, each possible number of channels occupied in a combinationof the U-NII-1 and U-NII-3 bands and a combination of the U-NII-2A andU-NII-2C bands. For example, the first chart shows that sampleaggregated Wi-Fi data 302 indicated that 12% of the map tiles 306 of NewYork County had all of the U-NII-1 and U-NII-3 channels free, while 29%of the map tiles 306 of New York County had all of the U-NII-1 andU-NII-3 channels occupied. The second chart shows that, from the samesample data, 25% of the map tiles 306 of New York County had all of theU-NII-2A and U-NII-2C channels free, while only 2% of the map tiles 306of New York County had all of the U-NII-1 and U-NII-3 channels occupied.The second chart also shows that, when combining the percentages of maptiles 306, 60% of the map tiles 306 had seven or fewer of the U-NII-2Aand U-NII-2C channels occupied (meaning that nine or more of thosechannels were free in 60% of the area of New York County).

If the underlying data shown in the charts and/or heat maps 500discussed above with respect to FIGS. 4-6 indicate that channels in oneor more specific bands are unlikely to interfere with Wi-Fitransmissions in a particular geographical area, those channels can beconsidered LAA-safe channels within that particular geographical area.For example, the heat maps 500 shown in FIG. 5A can show that one ormore channels in the U-NII-2C band are likely to be free in thegeographical area, while the heat maps 500 shown in FIG. 5B can showthat one or more channels in a combination of the U-NII-2A and U-NII-2Cbands are likely to be free in the geographical area. These example heatmaps 500 show that channels in a combination of the U-NII-2A andU-NII-2C bands are relatively free compared to a combination of thechannels in the U-NII-1 and U-NII-3 bands in this geographical area, andthat the channels in the U-NII-2A and U-NII-2C bands would haverelatively little risk of interfering with Wi-Fi signals in the mappedgeographical area compared to using channels in the U-NII-1 and U-NII-3bands.

In some examples, the server 118 can output charts, heat maps 500,and/or underlying data from the server's analysis for manual review toidentify LAA-safe channels. For example, such charts, heat maps 500,and/or other underlying data can be displayed in a user interface or beprinted out after they have been generated by the server 118. Such heatmaps, charts, and/or other data indicating LAA-safe channels can be usedto estimate bandwidth gain if those channels were used for LAAtransmissions.

The server 118 can also be configured to directly determine from ananalysis of the aggregated Wi-Fi data 302 that channels in a particularband, or a combination of bands, are safe to use for LAA transmissionsin a geographical area. In some examples, the server 118 can beconfigured to determine that channels of one or more bands are LAA-safewhen the total number of free channels, or a ratio of free channels to atotal number of channels, exceeds a predefined threshold value onaverage across the map tiles 306 covering the geographical area. Forexample, the server 118 can use data corresponding to heat maps 500 todetermine if the number of free channels in one or more bands exceedsone or more across the map tiles 306 covering a geographical area. Inother examples, the server 118 can be configured to determine thatchannels of one or more bands are LAA-safe when the percentage of maptiles 306 having at least a predefined number of free channels exceeds apredefined percentage. For example, in the example of FIG. 6 in whichnine or more channels of the U-NII-2A and U-NII-2C bands are free in 60%of the map tiles 306, if the predefined number of free channels is fourand the predefined percentage is 50%, the server 118 can determine thatthe U-NII-2A and U-NII-2C channels are LAA-safe. The server 118 mayprovide a recommendation regarding deployment of LAA-compatible hardwarebased on this analysis, and/or provide an estimate of a bandwidth gainusing such channels could provide if used for LAA transmissions.

After LAA-safe channels have been identified with respect to ageographical area by the server 118, or are identified based on arecommendation or other output generated by the server 118, thoseLAA-safe channels can be used for LAA transmissions in the geographicalarea. For example, an operator of the telecommunication network 106 candeploy LAA-capable base stations 104 in that geographical area that areconfigured to use identified LAA-safe channels for LAA transmissions.Alternately, or in addition, the server 118 or another element of thetelecommunication network 106 can send instructions to existingLAA-capable base stations 104 and/or UEs 102 located within thatgeographical area that change settings to enable options to use LAAtransmissions within that geographical area when appropriate.

In some examples, the server's analysis of aggregated Wi-Fi data 302 mayindicate that certain channels are LAA-safe channels, but are not yetsupported by UEs 102 or base stations 104. For example, some LAA-capablehardware, such as UEs 102 and/or base stations 104, may be nativelyconfigured to support potential use of the nine channels in the U-NII-1and U-NII-3 bands for LAA transmissions, but not the sixteen channels inthe U-NII-2A and U-NII-2C bands. However, as shown in the examples abovewith respect to FIG. 5B and FIG. 6, the server's analysis of aggregatedWi-Fi data 302 for a geographical area may show that the channels in theU-NII-2A and U-NII-2C bands are more likely to be free in thegeographical area than the channels in the U-NII-1 and U-NII-3 bands.Accordingly, a network operator or manufacturers of the UEs 102 or basestations 104 may initiate upgrades of the UEs 102 or base stations 104to also support LAA transmissions in the U-NII-2A and U-NII-2C bands, ormanufacture new versions of UEs 102 or base stations 104 that supportLAA transmissions in the U-NII-2A and U-NII-2C bands.

Although analysis discussed above with respect to FIGS. 4-6 can indicatewhen channels of one or more bands of the unlicensed spectrum 110 areLAA-safe with respect to one or more map tiles 306 because they are notbeing used by any Wi-Fi access points 112 in those map tiles 306, andaccordingly reflect a potential bandwidth gain that LAA transmissionsmay provide, in some situations channels may be LAA-safe even when thosechannels are being used by Wi-Fi access points 112. For example, denselypopulated areas may have a large number of Wi-Fi access points 112 thatin the aggregate have been set to use all of the candidate channels inthe 5 GHz band. However, although the Wi-Fi access points 112 may beusing all of the candidate channels to offer their Wi-Fi networks,actual utilization of those channels to send data via Wi-Fitransmissions may be low enough that LAA transmissions over thosechannels would not interfere with the Wi-Fi transmissions and thechannels can be considered LAA-safe and bandwidth gain could be achievedusing such LAA transmissions.

For example, if a particular channel is being utilized only 20% of thetime for Wi-Fi transmissions, then that channel is free 80% of the timesuch that LAA transmissions on that channel would not interfere withWi-Fi transmissions during that 80% of the time and bandwidth gain usingsuch LAA transmissions could be achieved. Accordingly, as shown in FIGS.7-14, the server 118 can use channel utilization information fromrecords 212 in aggregated Wi-Fi data 302 to help determine when theactual utilization of channels of one or more 5 GHz bands is low enoughin a geographical area to permit LAA transmissions over those channelsin the geographical area.

As shown in FIG. 7, aggregated Wi-Fi data 302 can include numerouscrowd-sourced records 212 submitted by UEs 102 in Wi-Fi reports 204. Asdiscussed above, each record 212 can include identifiers associated witha specific Wi-Fi access point 112, such as BSSIDs 206 and/or SSIDs 208,but can also include channel frequency 214 and BSS Load 210 data. Theserver 118 can use a record's channel frequency 214 data to identify achannel used by the Wi-Fi access point 112. For example, when a record'schannel frequency 214 is 5220 MHz, the server 118 can determine that thecorresponding channel is channel 44 (centered at 5220 MHz) as shown inthe example of FIG. 7.

The server 118 can also determine channel utilization 702 valuesassociated with each record 212 in the aggregated Wi-Fi data 302. Asdiscussed above, Wi-Fi access points 122 can include channel utilizationinformation about a percentage of time that a Wi-Fi access point 112sensed that the medium for its channel was busy within BSS Load 210elements of beacon signals 202. When channel utilization informationindicates that a channel used by a Wi-Fi access point 112 is busy for acertain percentage of the time, then the server 118 can determine thatduring the remainder of the time the channel is not being used for datatransmissions by that Wi-Fi access point 112 and would therefore be freefor LAA transmissions without the risk of interference 116. For example,when a Wi-Fi access point's channel utilization information indicatesthat a channel is busy 10% of the time, then during 90% of the time thechannel is likely to be free such that LAA transmissions would notinterfere with Wi-Fi transmissions associated with that Wi-Fi accesspoint 112.

For example, a Wi-Fi access point's channel utilization information canbe expressed in a middle byte of a five-byte section of a QBSS elementin a beacon signal 202. A beacon signal's BSS Load 210 can be includedin a record 212 of a Wi-Fi report 204, such that it becomes part of theaggregated Wi-Fi data 302. Accordingly, in this example the server 118can extract the byte of a record's BSS Load 210 element that correspondsto the channel utilization information and convert it from hexadecimalto decimal form to get a value normalized on a scale from 0 to 255. Theserver 118 can then calculate a percentage for the channel utilization702 based on dividing the decimal value by 255. For example, if themiddle byte of a five-byte BSS Load 210 element is the hexadecimal valueA4 (164 in decimal), the server 118 can determine that the channelutilization 702 is 64% (164/255), as shown in FIG. 7. In other examples,the server 118 can determine channel utilization 702 from other types ofdata, or receive channel utilization information in records 212 based onconversions performed by UEs 102. The server 118 can use the conversionprocesses described with respect to FIG. 7 to determine a channel andcorresponding channel utilizations 702 for multiple individual records212 having geolocation data 216 corresponding to a particular map tile306.

As shown in FIG. 8, the server 118 can use the channel and channelutilization 702 information for multiple individual records 212 havinggeolocation data 216 corresponding to a particular map tile 306 tocalculate an average channel utilization 802 within the map tile 306 forindividual channels that are candidates for LAA transmissions, such asthe channels of the four 5 GHz U-NII bands discussed above. In someexamples, the server 118 can use timestamp data in the records 212 tocalculate average channel utilization 802 values within a map tile 306for different channels at different times of day. For example, this mayshow that the average channel utilization is higher in the map tile 306for some or all channels during the middle of the day than at night. Anexample of time-based analysis of average channel utilization values isdiscussed in more detail below with respect to FIG. 14.

The server 118 can repeat the operations discussed above to determine anaverage channel utilization 802 for candidate channels in multiple maptiles 306, such as a set of map tiles 306 that cover the geographicalarea of a neighborhood, a city, a county, a state, or a country. Theaverage channel utilization 802 for candidate channels in multiple maptiles 306 can be analyzed by the server 118 in one or more ways.

As a first example of the server's analysis, the server 118 can generateheat maps similar to those discussed above with respect to FIGS. 5A and5B that indicate the average channel utilization 802 for one or morechannels within individual map tiles 306 that span a particulargeographical area. Such heat maps may indicate that a first set of oneor more channels has a lower average channel utilization 802 across mostof the map tiles 306 in the geographical area than a second set of oneor more channels, thereby indicating that sending LAA transmissionsusing the first set of channels has a lower chance of interfering withWi-Fi transmissions than LAA transmissions using the second set ofchannels in the geographical area.

As shown in the example of FIG. 9, the server 118 can also, oralternately, generate a chart that depicts the average channelutilization 802 across a set of map tiles 306 covering a geographicalarea with respect to multiple candidate channels for LAA transmissions.As shown in FIG. 9, the chart can also indicate a count of unique Wi-Fiaccess points 112 across the set of map tiles 306. In the example ofFIG. 9, the chart shows that the average channel utilization 802 isrelatively high in the normally-crowded 2.4 GHz band, for instance ataround 40% for the most commonly used channels 1, 6, and 11. However,although large numbers of Wi-Fi access points 112 use channels in the 5GHz band, especially in the U-NII-1 and U-NII-3 bands, those channelshave average channel utilization 802 values that are much lower than inin the 2.4 GHz band. For example, the channels in the U-NII-1, U-NII-2A,and U-NII-3 bands (and most of the channels of the U-NII-2C band) haveaverage channel utilization 802 values of under 10% even thoughrelatively large numbers of Wi-Fi access points 112 are using thosechannels.

Accordingly, the server 118 can be set to determine that channels of oneor more bands are LAA-safe in a set of map tiles 306 covering ageographical area when the average channel utilization 802 across theset of map tiles 306 is lower than a preset threshold value. Forexample, the server 118 can use data corresponding to heat maps ofaverage channel utilizations 802 to determine that individual channelsare LAA-safe when the average channel utilization 802 for the channelsis lower than 10%.

The server 118 can also, or alternately, determine sizes of total areascovered in the aggregate by multiple map tiles 306 that each share thesame average channel utilization 802 value for a channel. For example,FIG. 10 depicts a chart generated by the server 118 from exampleaggregated Wi-Fi data 302 for map tiles 306 covering New York County,and indicates the total square mileage of aggregated map tiles 306 thateach share the same average channel utilization 802 for 5 GHz channel 44in the U-NII-1 band. As shown in FIG. 10, in this example, aggregatedWi-Fi data 302 for map tiles 306 that had a 2% average channelutilization 802 had an aggregated total area of four square miles, andthe majority of the map tiles 306 covering the overall square mileage ofNew York County had average channel utilizations 802 of less than 10%.

In some examples, the server 118 can be set to determine that channelsof one or more bands are LAA-safe in a set of map tiles 306 when thepercentage or total aggregated size of map tiles 306 that have under athreshold average channel utilization value exceeds a threshold value.For example, in the example of FIG. 10, the server 118 can determinethat channel 44 is an LAA-safe channel because the aggregated area ofmap tiles 306 with under a 10% average channel utilization 802 exceeds athreshold value.

While the server's analysis can identify when individual channels areLAA-safe as discussed above, in some examples UEs 102 and/or basestations 104 can be configured to use carrier aggregation (CA) to sendLAA transmissions over multiple channels. For instance, the bandwidthavailable for LAA transmissions can be increased when CA is used to senddata over three consecutive neighboring channels in a 5 GHz U-NII band.As shown in FIG. 10, in some cases one channel may have a relativelyhigh average channel utilization 802, while neighboring channels mayhave lower average channel utilizations 802. Accordingly, the server 118can also determine probabilities of when at least a threshold number ofconsecutive neighboring channels in a band are expected to be free andLAA-safe.

As an example, when the server 118 is set to determine the probabilitythat three consecutive channels in the 5 GHz U-NII-1 band will be free,such that the three consecutive channels can be used for carrieraggregation when sending LAA transmissions, there are threepossibilities for the three consecutive channels that could be free: afirst set of channels that includes channels 36, 40, and 44, and asecond set of channels that includes channels 40, 44, and 48. The server118 can accordingly determine an average channel utilization 802 foreach of those channels across one or more map tiles 306 as discussedabove. Although average channel utilization 802 values for channels 36,40, 44, and 48 are often much lower as shown in FIG. 9, for explanationpurposes FIG. 11 depicts example data indicating that channel 36 has anaverage channel utilization 802 of 40%, channel 40 has an averagechannel utilization 802 of 50%, channel 44 has an average channelutilization 802 of 60%, and channel 48 has an average channelutilization 802 of 70%. Because the average channel utilization 802values can correspond to an average amount of time the channels are inuse, they can also indicate that the channels are likely to be freeduring the remainder of the time. Accordingly, the example averagechannel utilization 802 values shown in FIG. 11 can also indicate thatchannel 36 has a 60% chance of being free, channel 40 has a 50% chanceof being free, channel 44 has 40% chance of being free, and channel 48has a 30% chance of being free.

As shown in FIG. 11, the server 118 can use the average channelutilization 802 values for individual channels in a band to calculate aprobability of each possible set of three consecutive channels beingentirely free. For example, for a first possible set of threeconsecutive channels that includes channels 36, 40, and 44, the servercan multiply the 60% chance that channel 36 will be free by the 50%chance that channel 40 will be free by the 40% chance that channel 44will be free, to determine that there is a 12% chance of all three ofchannels 36, 40, and 44 being free. The server can repeat thesecalculations for the other possible set of three consecutive channels inthe U-NII-1 band that includes channels 40, 44, and 48.

Also as shown in the example of FIG. 11, the server 118 can use theprobabilities that all of channels in each possible set of threeconsecutive channels will be free to determine an overall probabilitythat at least three consecutive channels will be free in the band. Forexample, when a combination of channels 36, 40, and 44 has a 12% chanceof being free (and thereby a 88% chance of at least one of them beingused), and a combination of channels 40, 44, and 48 has a 6% chance ofbeing free (and thereby a 94% chance of at least one of them beingused), the server 118 can multiply the chances of that at least onechannel in each set will be in use and subtract the result from 1, todetermine that there is a 17.28% chance that at least three consecutivechannels in the U-NII-1 band (channels 36, 40, 44, and 48) will be free.The server 118 can repeat these calculations for channels in the otherU-NII bands. In some examples, the server 118 can generate charts, heatmaps, and/or other representations of the probabilities described above.

Although the example of FIG. 11 shows the server 118 finding that thereis a 17.28% chance of three or more channels in the U-NII-1 band will befree, in many cases the aggregated Wi-Fi data 302 can show much higherchances of three or more channels in the U-NII-1 band being free. Forexample, although the calculations shown in FIG. 11 are based on exampledata in which the channels of the U-NII-1 band have average channelutilization 802 values ranging from 40% to 70%, in many cases thosechannels may be found to have lower average channel utilization 802values, and thus higher chances of the channels being free. For example,FIG. 9 shows an example in which the channels of the U-NII-1 band haveaverage channel utilization 802 values ranging from 3.8% to 4.0%. If amap tile 306 had those lower average channel utilization 802 values forchannels 36, 40, 44, and 48, then the probabilities of the sets of threeconsecutive channels being free, and the overall probability of at leastthree consecutive channels being free in the U-NII-1 band, would behigher.

The server 118 can determine sizes of total areas covered in theaggregate by multiple map tiles 306 that each share the same probabilityof having a particular set of consecutive channels free. For example,FIG. 12 depicts a chart generated by the server 118 from exampleaggregated Wi-Fi data 302 for map tiles 306 covering New York County,and indicates the total square mileage of aggregated map tiles 306 thateach share the same probability of having channels 36, 40, and 44 freein the U-NII-1 band.

As mentioned above, the server 118 can also determine the probabilitiesof having at least three consecutive channels free in a band based onthe probabilities of having each possible set of three consecutivechannels free within that band. For example, the server 118 can combinea map tile's probability of having channels 36, 40, and 44 free with themap tile's probability of having channels 40, 44, and 48 free todetermine the map tile's overall probability of having at least threeconsecutive channels free in the U-NII-1 band. The server 118 candetermine the probabilities of having at least three consecutivechannels free in pone or more bands for multiple map tiles 306.Accordingly, the server 118 can determine sizes of total areas coveredin the aggregate by multiple map tiles 306 that each share the sameprobability of having at least three consecutive channels free in one ormore bands. For example, FIG. 13 depicts charts generated by the server118 from example aggregated Wi-Fi data 302 for map tiles 306 coveringNew York County, with a first chart indicating the total square mileageof aggregated map tiles 306 that each share the same probability ofhaving three or more channels free in the U-NII-1 band, and a secondchart indicating the total square mileage of aggregated map tiles 306that each share the same probability of having three or more channelsfree in the U-NII-2A band.

In some examples, the server 118 can output charts, heat maps, and/orunderlying data from the server's analysis as discussed above withrespect to FIGS. 9-13 for manual review to identify LAA-safe channels.For example, such charts, heat maps, and/or other underlying data can bedisplayed in a user interface or be printed out after they have beengenerated by the server 118. Such heat maps, charts, and/or other dataindicating LAA-safe channels can be used to estimate bandwidth gain ifthose channels were used for LAA transmissions.

The server 118 can also be configured to directly determine from ananalysis of the aggregated Wi-Fi data 302 as described above withrespect to FIGS. 9-13 that channels in a particular band, or acombination of bands, are safe to use for LAA transmissions in ageographical area. For example, the server 118 can be set to determinethat channels or bands are LAA-safe when average utilization values 802for channels are below 10%, such that the server 118 would find majorityof the 5 GHz U-NII channels are LAA-safe when the server 118 finds theaverage utilization values 802 shown in FIG. 9. The server 118 mayprovide a recommendation regarding deployment of LAA-compatible hardwarebased on this analysis, and/or provide an estimate of a bandwidth gainusing such channels could provide if used for LAA transmissions.

As another example, the server 118 can be set to determine that bands ofchannels are LAA-safe for CA when the CA analysis described aboveindicates that the probability of having at least a threshold number ofconsecutive channels free in a band exceeds a threshold value. Forexample, the server 118 can be configured to determine that bands areLAA-safe when there is at least at 90% chance that three consecutivechannels will be free within a set of map tiles 306, such that theserver 118 would find the U-NII-1 and U-NII-2A bands to be LAA-safe forCA based on the charts shown in FIG. 13. The server 118 may provide arecommendation regarding deployment of LAA-compatible hardware based onthis analysis, and/or provide an estimate of a bandwidth gain using suchchannels could provide if used for LAA transmissions via CA.

As mentioned above, although the server 118 can perform the analysesdescribed above from records 212 with respect to a geographical areaover a certain period of time, in some examples the server 118 canperform these analyses based on records 212 corresponding to differentperiods of time to determine whether channels may be considered LAA-safeduring some periods of time and not others.

For example, FIG. 14 shows results of a server's analysis of records 212from map tiles 306 covering the location of a convention center atvarious times of day. In the example of FIG. 14, the top chart showshourly average channel utilization 802 values within the map tiles 306for channel 36, and indicates that usage of channel 36 is much heavierduring the middle of the day, especially near the lunch hour.Accordingly, the server 118 may determine that if the records 212 showhigh channel utilization values of some or all channels during periodswhen a convention is occurring, but low channel utilization values atother times, those channels should not be considered LAA-safe in the maptiles 306 covering the convention center when a convention is scheduled.The server 118, or other element of the telecommunication network 106,can instruct base stations 104 near the map tiles 306 covering theconvention center not to use LAA during those times, or personnel cansimilarly configure the base stations 104 based on review of output fromthe server 118.

As another example, the bottom chart of FIG. 14 shows probabilitiescalculated by the server 118 that three of more consecutive channels inthe U-NII-1 and U-NII-3 bands will not be free in the map tiles 306covering the convention center, and would thus not be available for CALAA transmissions. For instance, the chances that three or moreconsecutive channels in the U-NII-1 band will not be free are relativelyhigh, especially between 9 AM and 1 PM. However, the bottom chart ofFIG. 14 shows that the chances that three or more consecutive channelsin the U-NII-3 band will not be free are relatively low, even during themiddle of the day. Accordingly, the server 118, another element of thetelecommunication network 106, or network personnel may configure basestations 104 near the map tiles 306 covering the convention center notto use CA for LAA transmissions with channels in the U-NII-1 band from 9AM to 1 PM when conventions are scheduled, but permit the base stations104 to use CA for LAA transmissions with channels in the U-NII-3 bandduring some or all of those hours.

In addition, in some examples the server 118 can use information aboutboth the number of unique Wi-Fi access points 112 in a set of map tiles306 and channel utilization information for those map tiles 306 topredict the likelihood of interference 116 in the future. The server'sdetermination of a number of unique Wi-Fi access points 118 is discussedabove with respect to FIG. 4. For example, the server 118 may determinethat a first location with one hundred unique Wi-Fi access points 112has a higher likelihood of interference 116 than a second location thathas only one unique Wi-Fi access point 112, even if the channelutilization values are similar. Accordingly, the server's output mayindicate or recommend that LAA not be deployed in the first location dueto the higher likelihood of interference 116, but be deployed in thesecond location despite similar channel utilization values in the twolocations.

Although the server 118 is described herein as analyzing data withrespect to channels of the 5 GHz band, in some examples the server 118can use the same methods to collect Wi-Fi records 204 with respect tochannels 2.4 GHz spectrum, such that those channels can also be analyzedas described herein. For example, FIG. 9 indicates that the server 118has collected Wi-Fi reports 204 containing records 212 associated withboth 2.4 GHz channels and 5 GHz channels and has found numbers of uniqueWi-Fi access points 112 and average channel utilization 802 values for2.4 GHz channels and 5 GHz channels. The server 118 can accordingly useits analysis of 2.4 GHz channels and 5 GHz channels to compare thelikelihood of LAA transmissions interfering with Wi-Fi transmissionsacross different combinations of channels.

Example Architecture

FIG. 15 depicts an example system architecture for a UE 102, inaccordance with various examples. As shown, a UE 102 can include amemory 1502 that stores a Wi-Fi scanning application 1504 and othermodules and data 1506, processor(s) 1508, radio interfaces 1510, adisplay 1512, output devices 1514, input devices 1516, and/or a driveunit 1518 including a machine readable medium 1520.

In various examples, memory 1502 can include system memory, which may bevolatile (such as RAM), non-volatile (such as ROM, flash memory, etc.)or some combination of the two. Memory 1502 can further includenon-transitory computer-readable media, such as volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information, such as computer readableinstructions, data structures, program modules, or other data. Systemmemory, removable storage, and non-removable storage are all examples ofnon-transitory computer-readable media. Examples of non-transitorycomputer-readable media include, but are not limited to, RAM, ROM,EEPROM, flash memory or other memory technology, CD-ROM, digitalversatile discs (DVD) or other optical storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or any other non-transitory medium which can be used to store thedesired information and which can be accessed by the UE 102. Any suchnon-transitory computer-readable media may be part of the UE 102.

The memory 1502 can store computer-readable instructions and/or otherdata associated with a Wi-Fi scanning application 1504 configured toautomatically scan for beacon signals 202 and submit Wi-Fi reports 204to the server 118 as described above. In some examples, the Wi-Fiscanning application 1504 can be an application provided to the UE 102by the server 118 or another element of the telecommunication network106. For example, the telecommunication network 106 can use over-the-airupdates or other distribution methods to provide the UE 102 with theWi-Fi scanning application 1504. In some examples, the Wi-Fi scanningapplication 1504 can be part of a larger application with otherfeatures. For example, the Wi-Fi scanning application 1504 can be partof an application provided by the operator of the telecommunicationnetwork 106 that allows users to check their data usage, change theirservice plan, or access other information about their accounts with theoperator of the telecommunication network 106. In other examples, theWi-Fi scanning application 1504 can be part of the UE's firmware oroperating system, and/or be other computer-executable instructions thatcause hardware and/or software components of the UE 102 to scan forbeacon signals 202 and submit Wi-Fi reports 204 to the server 118.

The memory 1502 can also store other modules and data 1506 that can beutilized by the UE 102 to perform or enable performing any action takenby the UE 102. The modules and data 1506 can include a UE platform andapplications, and data utilized by the platform and applications.

In various examples, the processor(s) 1508 can be a central processingunit (CPU), a graphics processing unit (GPU), or both CPU and GPU, orany other type of processing unit. Each of the one or more processor(s)1508 may have numerous arithmetic logic units (ALUs) that performarithmetic and logical operations, as well as one or more control units(CUs) that extract instructions and stored content from processor cachememory, and then executes these instructions by calling on the ALUs, asnecessary, during program execution. The processor(s) 1508 may also beresponsible for executing all computer applications stored in the memory1502, which can be associated with common types of volatile (RAM) and/ornonvolatile (ROM) memory.

The radio interfaces 1510 can include transceivers, modems, interfaces,antennas, and/or other components that perform or assist with scans forbeacon signals 202 or other wireless communications with base stations104 and/or Wi-Fi access points 112. For example, the UE 102 can haveradio interfaces 1510 compatible with LTE, Wi-Fi, and/or any other typeof wireless connection. In some examples, the UE 102 can also have wireddata connection components that allow wired data connections to theInternet and/or other networks.

The display 1512 can be a liquid crystal display or any other type ofdisplay commonly used in UEs 102. For example, display 1512 may be atouch-sensitive display screen, and can then also act as an input deviceor keypad, such as for providing a soft-key keyboard, navigationbuttons, or any other type of input.

The output devices 1514 can include any sort of output devices known inthe art, such as a display 1512, speakers, a vibrating mechanism, and/ora tactile feedback mechanism. Output devices 1514 can also include portsfor one or more peripheral devices, such as headphones, peripheralspeakers, and/or a peripheral display.

The input devices 1516 can include any sort of input devices known inthe art. For example, input devices 1516 can include a microphone, akeyboard/keypad, and/or a touch-sensitive display, such as thetouch-sensitive display screen described above. A keyboard/keypad can bea push button numeric dialing pad, a multi-key keyboard, or one or moreother types of keys or buttons, and can also include a joystick-likecontroller, designated navigation buttons, or any other type of inputmechanism.

The machine readable medium 1520 can store one or more sets ofinstructions, such as software or firmware, that embodies any one ormore of the methodologies or functions described herein. Theinstructions can also reside, completely or at least partially, withinthe memory 1502, processor(s) 1508, and/or radio interface(s) 1510during execution thereof by the UE 102. The memory 1502 and theprocessor(s) 1508 also can constitute machine readable media 1520.

FIG. 16 depicts an example system architecture of a server 118. Theserver 118 can be a computing device that has a system memory 1602. Thesystem memory 1602 can store data for the server 118, including a Wi-Fireport aggregator 1604, a Wi-Fi data analyzer 1606, an LAA deploymentmanager 1608, and/or other modules and data 1610. The server 118 canalso include processor(s) 1612, removable storage 1614, non-removablestorage 1616, input device(s) 1618, output device(s) 1620, and/orcommunication connections 1622 for communicating with other networkelements 1624.

In various examples, system memory 1602 can be volatile (such as RAM),non-volatile (such as ROM, flash memory, etc.), or some combination ofthe two. Example system memory 1602 can include one or more of RAM, ROM,EEPROM, a Flash Memory, a hard drive, a memory card, an optical storage,a magnetic cassette, a magnetic tape, a magnetic disk storage or anothermagnetic storage devices, or any other medium.

The Wi-Fi report aggregator 1604 can receive Wi-Fi reports 204 submittedby UEs 102 and use them to generate aggregated Wi-Fi data 302. In someexamples, the Wi-Fi report aggregator 1604 can generate a master set ofaggregated Wi-Fi data 302, but be configured to filter or search themaster set to obtain records 212 corresponding to desired time periods,geographical locations, and/or any other criteria. For example, theWi-Fi report aggregator 1604 can be configured to find records 212 inthe aggregated Wi-Fi data that are specific to individual map tiles 306or a set of map tiles 306 covering a particular geographical area. Inother examples, the Wi-Fi report aggregator 1604 can generate differentsets of aggregated Wi-Fi data 302 that are specific to certain periodsof time, geographical locations, and/or any other criteria.

The Wi-Fi data analyzer 1606 can use records in aggregated Wi-Fi data302 to generate data that can determine whether one or more channels ofthe unlicensed spectrum 110 are LAA-safe. In various examples, the Wi-Fidata analyzer 1606 can determine numbers of unique Wi-Fi access points112 that are using individual channels in one or more map tiles 306,whether individual channels are free in one or more map tiles, determinechannel utilization 702 values for individual records 212, determineaverage channel utilization 802 values for one or more map tiles 306,and/or determine the probabilities of at least a threshold number ofconsecutive channels being free in one or more bands with respect to oneor more map tiles 306. The Wi-Fi data analyzer 1606 can be configured tocompare the counts, values, and/or probabilities it generates againstthreshold values to directly identify whether certain channels or bandsin the unlicensed spectrum 110 are LAA-safe in one or more map tiles306. The Wi-Fi data analyzer 1606 can also be configured to output heatmaps, charts, and/or other types of data that can illustrate the counts,values, and/or probabilities it generates. The Wi-Fi data analyzer 1606can be configured to analyze aggregated Wi-Fi data 302 across any timeperiod, such as days or weeks, or more granularly such as hour by hour.

The LAA deployment manager 1608 can, based on a determination from theWi-Fi data analyzer or other source that one or more channels of theunlicensed spectrum 110 are LAA-safe with respect to one or more maptiles 306, provide a recommendation or other output indicating thatLAA-capable base stations 104 that can use the LAA-safe channels for LAAtransmissions with UEs 102 can be deployed to cover those map tiles 306.For example, recommendations output by the LAA deployment manager 1608can be instructions or other information for LAA hardware deployment,and may identify which channels should be used for LAA transmissionsand/or restrictions on their use, such as during specific times of day.The recommendations may also provide an estimate of the bandwidth gainsuch LAA transmissions could provide. In other examples, the LAAdeployment manager 1608 may, based on the server's determinations thatchannels are LAA-safe in the geographical area, output instructions tobase stations 104 and/or UEs 102 that enable options or settings to useLAA transmissions when appropriate in the geographical area.

The other modules and data 1610 can be utilized by the server 118 toperform or enable performing any action taken by the server 118. Theother modules and data 1610 can include a platform and applications, anddata utilized by the platform and applications.

In some embodiments, the processor(s) 1612 can be a central processingunit (CPU), a graphics processing unit (GPU), both CPU and GPU, or otherprocessing unit or component known in the art.

The server 118 can also include additional data storage devices(removable and/or non-removable) such as, for example, magnetic disks,optical disks, or tape. Such additional storage is illustrated in FIG.16 by removable storage 1614 and non-removable storage 1616. Computerstorage media may include volatile and nonvolatile, removable andnon-removable media implemented in any method or technology for storageof information, such as computer readable instructions, data structures,program modules, or other data. System memory 1602, removable storage1614 and non-removable storage 1616 are all examples ofcomputer-readable storage media. Computer-readable storage mediainclude, but are not limited to, RAM, ROM, EEPROM, flash memory or othermemory technology, CD-ROM, digital versatile discs (DVD) or otheroptical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to store the desired information and which can be accessed bythe server 118. Any such computer-readable storage media can be part ofthe server 118. In various examples, any or all of system memory 1602,removable storage 1614, and non-removable storage 1616, storeprogramming instructions which, when executed, implement some or all ofthe herein-described operations of the server 118.

In some examples, the server 118 can also have input device(s) 1618,such as a keyboard, a mouse, a touch-sensitive display, voice inputdevice, etc., and/or output device(s) 1620 such as a display, speakers,a printer, etc. These devices are well known in the art and need not bediscussed at length here.

The server 118 can also contain communication connections 1622 thatallow the server 118 to communicate with other network elements 1624such as UEs 102, base stations 104, and other elements of thetelecommunication network 106. For example, the server 118 can receiveWi-Fi reports 204 from UEs 102 via the communication connections 1622.

Example Operations

FIG. 17 depicts a flow chart of a first method for identifying LAA-safechannels in one or more bands of the unlicensed spectrum 110. In someexamples, the method of FIG. 17 can be used to evaluate, with respect toa geographical area, whether candidate LAA channels are LAA-safe, suchas 5 GHz candidate LAA channels in the U-NII-1, U-NII-2A, U-NII-2C,and/or U-NII-3 bands.

At block 1702, a server 118 can identify records 212 from crowd-sourcedWi-Fi reports 204 submitted by UEs 102 that correspond to a map tile 306within the geographical area. The records 212 can be filtered from amaster set of aggregated Wi-Fi data 302 built from the crowd-sourcedWi-Fi reports 204, or retrieved from a set of aggregated Wi-Fi data 302that is specific to the geographical area. The records 212 can includegeolocation data 216 indicating that they correspond to scans for beaconsignals 202 that were performed by UEs 102 within an area covered by themap tile 306.

At block 1704, the server 118 can identify unique Wi-Fi access points112 within the set of records found at block 1702. For example, theserver 118 can use BSSIDs 206, SSIDs 208, and/or other data in therecords 212 that identify the records 212 as corresponding to beaconsignals 202 broadcast by different Wi-Fi access points 112.

At block 1706, the server 118 can use channel frequency 214 data in therecords 212 to count how many of unique Wi-Fi access points 112 wereusing each of the candidate LAA channels.

At block 1708, the server 118 can use the number of unique Wi-Fi accesspoints 112 that were using each of the candidate LAA channels in aparticular band, relative to the total number of candidate LAA channelsin that band, to determine how many candidate LAA channels in that bandare free and not being used by any Wi-Fi access points 112 in the maptile 306.

At block 1710, the server 118 can determine if records 212 from anyother map tiles 306 in the geographical area have not yet been analyzedat blocks 1702-1708. If records 212 from other map tiles 306 are stillto be analyzed, the server 118 can repeat blocks 1702-1708 for therecords 212 from those map tiles 306. If records 212 from all of the maptiles 306 covering the geographical area are been analyzed at blocks1702-1708, the server 118 can continue to block 1712.

At block 1712, the server 118 can use the number of candidate LAAchannels that are free in one or more bands, as determined at block1708, to identify which of those candidate LAA channels, if any, areLAA-safe in the geographical area. In some examples, at block 1714 theserver 118 can generate heat maps 500 showing the number of freecandidate LAA channels in one or more bands with respect to differentmap tiles 306 covering the geographical area, which can be used todetermine if certain candidate LAA channels or bands are LAA-safe acrossthe geographical area. In some examples, at block 1716 the server 118can generate charts, for example as discussed above with respect to FIG.6, that indicate a total size or percentage of the map tiles 306 thathave each number of candidate LAA channels in one or more bandsoccupied.

In some examples, the server 118 can compare the counts or percentagesit generates with respect to candidate LAA channels and/or bands overone or more map tiles against threshold values, and if the counts orpercentages meet the threshold values, the server 118 can determine thatthe candidate LAA channels and/or bands are LAA-safe in the geographicalarea.

At block 1718, after identification of LAA-safe channels, the server 118can output information indicating that LAA-capable base stations 104 canbe deployed and/or enabled in the geographical area to use the LAA-safechannels when exchanging LAA transmissions. For example, the server 118can output identifications of the LAA-safe channels for the geographicalarea, heat maps, charts, estimates of gains that LAA transmissions overthe LAA-safe channels would provide, deployment recommendations, settingchanges, and/or any other output. Accordingly, based on the output, basestations 104 can be installed, upgraded, or reconfigured in thegeographical area to permit LAA transmissions using the LAA-safechannels.

FIG. 18 depicts a flow chart of a second method for identifying LAA-safechannels in one or more bands of the unlicensed spectrum 110. In someexamples, the method of FIG. 18 can be used to evaluate, with respect toa geographical area, whether candidate LAA channels are LAA-safe, suchas 5 GHz candidate LAA channels in the U-NII-1, U-NII-2A, U-NII-2C,and/or U-NII-3 bands.

At block 1802, a server 118 can identify records 212 from crowd-sourcedWi-Fi reports 204 submitted by UEs 102 that correspond to a map tile 306within the geographical area. The records 212 can be filtered from amaster set of aggregated Wi-Fi data 302 built from the crowd-sourcedWi-Fi reports 204, or retrieved from a set of aggregated Wi-Fi data 302that is specific to the geographical area. The records 212 can includegeolocation data 216 indicating that they correspond to scans for beaconsignals 202 that were performed by UEs 102 within an area covered by themap tile 306.

At block 1804, the server 118 can determine a channel and a channelutilization 702 value associated with each record 212. For example, arecord 212 can include a channel frequency 214 at which a correspondingbeacon signal 202 was received, and the server 118 can find a channelthat maps to that channel frequency 214. A record 212 can also include aBSS Load 210 element that can express channel utilization information.For example, a record's BSS Load 210 element can be a QBSS Load elementthat has channel utilization information included as a middle byte of afive-byte sequence. Accordingly, the server 118 can extract that byteand convert it to a channel utilization 702 value.

At block 1806, after having determined channels and channel utilization702 values for each record 212, the server 118 can average the channelutilization 702 values to calculate an average channel utilization 802for each candidate LAA channel in the map tile 306.

At block 1808, the server 118 can determine if records 212 from anyother map tiles 306 in the geographical area have not yet been analyzedat blocks 1802-1806. If records 212 from other map tiles 306 are stillto be analyzed, the server 118 can repeat blocks 1802-1806 for therecords 212 from those map tiles 306. If records 212 from all of the maptiles 306 covering the geographical area are been analyzed at blocks1802-1806, the server 118 can continue to block 1810.

At block 1810, the server 118 can use the average channel utilization802 values for the candidate LAA channels, as determined at block 1806,to identify which of those candidate LAA channels, if any, are LAA-safein the geographical area. In some examples, at block 1812 the server 118can generate heat maps showing the average channel utilization 802values for channels of one or more bands with respect to different maptiles 306 covering the geographical area, which can be used to determineif certain candidate LAA channels or bands are LAA-safe across thegeographical area. In some examples, at block 1814 the server 118 cangenerate charts. For example, the server 118 can generate a chart asdiscussed above with respect to FIG. 8 that indicates the averagechannel utilization 802 with respect to multiple candidate LAA channels,which can be used to determine if certain candidate LAA channels orbands are LAA-safe across the geographical area. As another example, theserver 118 can generate an area chart indicating a total size orpercentage of the map tiles 306 that have a common average channelutilization 802 value, which can be used to determine if certaincandidate LAA channels or bands are LAA-safe across the geographicalarea.

In some examples, the server 118 can compare the average channelutilization 802 values it generates with respect to candidate LAAchannels and/or bands over one or more map tiles against thresholdpercentages, and if the average channel utilization 802 values meet thethreshold percentages, the server 118 can determine that the candidateLAA channels and/or bands are LAA-safe in the geographical area.

At block 1816, after identification of LAA-safe channels, the server 118can output information indicating that LAA-capable base stations 104 canbe deployed and/or enabled in the geographical area to use the LAA-safechannels when exchanging LAA transmissions. For example, the server 118can output identifications of the LAA-safe channels for the geographicalarea, heat maps, charts, estimates of gains that LAA transmissions overthe LAA-safe channels would provide, deployment recommendations, settingchanges, and/or any other output. Accordingly, based on the output, basestations 104 can be installed, upgraded, or reconfigured in thegeographical area to permit LAA transmissions using the LAA-safechannels.

FIG. 19 depicts a flow chart of a method for identifying LAA-safe bandsof channels in the unlicensed spectrum 110 in which at least apredetermined number of consecutive channels are expected to be free forcarrier aggregation (CA) during LAA transmissions. In some examples, themethod of FIG. 19 can be used to evaluate, with respect to ageographical area, whether three or more consecutive candidate LAAchannels are likely to be free, for example in the 5 GHz U-NII-1,U-NII-2A, U-NII-2C, and/or U-NII-3 bands.

At block 1902, a server 118 can identify records 212 from crowd-sourcedWi-Fi reports 204 submitted by UEs 102 that correspond to a map tile 306within the geographical area. The records 212 can be filtered from amaster set of aggregated Wi-Fi data 302 built from the crowd-sourcedWi-Fi reports 204, or retrieved from a set of aggregated Wi-Fi data 302that is specific to the geographical area. The records 212 can includegeolocation data 216 indicating that they correspond to scans for beaconsignals 202 that were performed by UEs 102 within an area covered by themap tile 306.

At block 1904, the server 118 can determine a channel and a channelutilization 702 value associated with each record 212. For example, arecord 212 can include a channel frequency 214 at which a correspondingbeacon signal 202 was received, and the server 118 can find a channelthat maps to that channel frequency 214. A record 212 can also include aBSS Load 210 element that can express channel utilization information.For example, a record's BSS Load 210 element can be a QBSS Load elementthat has channel utilization information included as a middle byte of afive-byte sequence. Accordingly, the server 118 can extract that byteand convert it to a channel utilization 702 value.

At block 1906, after having determined channels and channel utilization702 values for each record 212, the server 118 can average the channelutilization 702 values to calculate an average channel utilization 802for each candidate LAA channel in the map tile 306.

At block 1908, the server 118 can determine if records 212 from anyother map tiles 306 in the geographical area have not yet been analyzedat blocks 1902-1906. If records 212 from other map tiles 306 are stillto be analyzed, the server 118 can repeat blocks 1902-1906 for therecords 212 from those map tiles 306. If records 212 from all of the maptiles 306 covering the geographical area are been analyzed at blocks1902-1906, the server 118 can continue to block 1910.

At block 1910, the server 118 can use the average channel utilization802 values for the candidate LAA channels, as determined at block 1906,to determine probabilities that at least three (or any other desirednumber) of consecutive channels will be free in one or more bands. Asdiscussed above with respect to FIG. 11, the server 118 can calculateprobabilities that each possible set of three consecutive channels willbe free in a band, then combine those probabilities to find an overallprobability that three of more consecutive channels will be free in theband.

At block 1912, the server 118 can identify which bands, if any, haveLAA-safe channels in the geographical area for CA transmissions via LAA,based on the probabilities of at least three (or any other desirednumber) of consecutive candidate LAA channels being free in the band. Insome examples, at block 1914 the server 118 can generate heat mapsshowing the probabilities of at least three consecutive candidate LAAchannels being free in one or more bands, which can be used to determineif certain bands are LAA-safe for CA transmissions via LAA across thegeographical area. In some examples, at block 1916 the server 118 cangenerate charts. For example, the server 118 can generate charts asdiscussed above with respect to FIG. 13 that indicate a total size orpercentage of the map tiles 306 that have a common probability of havingat least three consecutive candidate LAA channels free in one or morebands, which can be used to determine if certain bands are LAA-safe forCA transmissions via LAA across the geographical area.

In some examples, the server 118 can compare the probabilities of atleast three consecutive candidate LAA channels being free in one or morebands over one or more map tiles against threshold probabilities, and ifthe probabilities meet the threshold probabilities, the server 118 candetermine that the candidate LAA bands are LAA-safe in the geographicalarea.

At block 1918, after identification of LAA-safe bands for CAtransmissions via LAA, the server 118 can output information indicatingthat LAA-capable base stations 104 can be deployed and/or enabled in thegeographical area to use the LAA-safe bands when using CA to exchangeLAA transmissions. For example, the server 118 can outputidentifications of the LAA-safe bands for the geographical area, heatmaps, charts, estimates of gains that CA-based LAA transmissions wouldprovide, deployment recommendations, setting changes, and/or any otheroutput. Accordingly, based on the output, base stations 104 can beinstalled, upgraded, or reconfigured in the geographical area to permitCA transmissions using channels of the LAA-safe bands.

CONCLUSION

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter is not necessarily limited to the specificfeatures or acts described above. Rather, the specific features and actsdescribed above are disclosed as example embodiments.

What is claimed is:
 1. A method comprising: receiving, by a computingdevice associated with a telecommunication network, a plurality ofrecords from plurality of user equipments (UEs) that include informationabout Wi-Fi networks offered by Wi-Fi access points over channels of anunlicensed spectrum and geolocation data indicating where individualones of the plurality of UEs detected the Wi-Fi networks; identifying,by the computing device, a set of the plurality of records in which thegeolocation data corresponds to a geographical area; determining, by thecomputing device, average channel utilization values for individual onesof the channels within the geographical area based on channelutilization information in the set of the plurality of records; andgenerating, by the computing device, output data indicating thatLicensed Assisted Access (LAA) transmissions using Long-Term Evolution(LTE) protocols over one or more of the channels of the unlicensedspectrum will not interfere with Wi-Fi transmissions using the one ormore channels within the geographical area, wherein the output dataincludes an estimate of a bandwidth gain that would be provided by theLAA transmissions.
 2. The method of claim 1, further comprising:determining, by the computing device, a probability of at least apredefined number of consecutive channels being free in a band withinthe geographical area based on the average channel utilization values;and determining, by the computing device, that the probability of atleast a predefined number of consecutive channels being free in a bandwithin the geographical area exceeds a threshold percentage, wherein theoutput indicates that the one or more of the channels of the unlicensedspectrum are in the band and can be used for carrier aggregation in theband during the LAA transmissions.
 3. The method of claim 1, wherein theoutput data includes an instruction to one or more base stations of thetelecommunication network proximate to the geographical area thatpermits the one or more base stations to use one or more of the channelsof the unlicensed spectrum during the LAA transmissions with individualones of the plurality of UEs.
 4. The method of claim 1, wherein theoutput data includes a heat map that plots the average channelutilization values associated with the one or more channels over thegeographical area.
 5. The method of claim 1, wherein the output dataincludes a chart that indicates the average channel utilization valuesfor the individual ones of the channels within the geographical area. 6.The method of claim 1, wherein the output data includes a chart thatindicates portions of the geographical area that correspond to commonones of the average channel utilization values associated with the oneor more channels.
 7. The method of claim 1, wherein the computing deviceperforms the identifying, the determining, and the generating based onsubsets of the set of records that correspond to individual ones of aplurality of map titles covering the geographical area.
 8. The method ofclaim 1, wherein the channels of the unlicensed spectrum are channels ina 5 GHz band.
 9. The method of claim 1, wherein determining the averagechannel utilization values for individual ones of the channels withinthe geographical area comprises: identifying, by the computing device,channels associated with individual ones of the set of the plurality ofrecords based on channel frequency information included in the set ofthe plurality of records; calculating, by the computing device, channelutilization values for the individual ones of the set of the pluralityof records based on the channel utilization information; and averaging,by the computing device, the channel utilization values for individualones of the channels to generate the average channel utilization values.10. The method of claim 9, wherein the channel frequency information isincluded within Basic Service Set (BSS) Load elements of the pluralityof records.
 11. The method of claim 1, wherein the computing devicegenerates the output data with respect to the channels of the unlicensedspectrum for a plurality of different time periods.
 12. A computingdevice, comprising: one or more processors; and memory storingcomputer-executable instructions that, when executed by the one or moreprocessors, cause the computing device to: receive a plurality ofrecords from plurality of user equipments (UEs) that include informationabout Wi-Fi networks offered by Wi-Fi access points over channels of anunlicensed spectrum and geolocation data indicating where individualones of the plurality of UEs detected the Wi-Fi networks; identify a setof the plurality of records in which the geolocation data corresponds toa geographical area; determine average channel utilization values forindividual ones of the channels within the geographical area based onchannel utilization information in the set of the plurality of records;generate output data indicating that Wi-Fi transmissions over one ormore of the channels of the unlicensed spectrum are below a thresholdvalue such that Licensed Assisted Access (LAA) transmissions usingLong-Term Evolution (LTE) protocols may operate over the one or more ofthe channels of the unlicensed spectrum; determine a probability of atleast a predefined number of consecutive channels being free in a bandwithin the geographical area based on the average channel utilizationvalues; and determine that the probability of at least a predefinednumber of consecutive channels being free in a band within thegeographical area exceeds a threshold percentage, wherein the outputdata indicates that the one or more of the channels of the unlicensedspectrum are in the band and can be used for carrier aggregation in theband during the LAA transmissions.
 13. The computing device of claim 12,wherein the output data includes an instruction to one or more basestations of a telecommunication network proximate to the geographicalarea that permits the one or more base stations to use one or more ofthe channels of the unlicensed spectrum during the LAA transmissionswith individual ones of the plurality of UEs.
 14. The computing deviceof claim 12, wherein the output data includes at least one of a heat mapthat plots the average channel utilization values associated with theone or more channels over the geographical area, a first chart thatindicates the average channel utilization values for the individual onesof the channels within the geographical area, or a second chart thatindicates portions of the geographical area that correspond to commonones of the average channel utilization values associated with the oneor more channels.
 15. One or more non-transitory computer-readable mediastoring computer-executable instructions that, when executed by one ormore processors of a computing device, cause the computing device toperform operations comprising: receiving a plurality of records fromplurality of user equipments (UEs) that include information about Wi-Finetworks offered by Wi-Fi access points over channels of an unlicensedspectrum and geolocation data indicating where individual ones of theplurality of UEs detected the Wi-Fi networks; identifying a set of theplurality of records in which the geolocation data corresponds to ageographical area; determining average channel utilization values forindividual ones of the channels within the geographical area based onchannel utilization information in the set of the plurality of records;generating output data indicating that Wi-Fi transmissions over one ormore of the channels of the unlicensed spectrum are below a thresholdvalue such that Licensed Assisted Access (LAA) transmissions usingLong-Term Evolution (LTE) protocols may operate over the one or more ofthe channels of the unlicensed spectrum; determining a probability of atleast a predefined number of consecutive channels being free in a bandwithin the geographical area based on the average channel utilizationvalues; and determining that the probability of at least a predefinednumber of consecutive channels being free in a band within thegeographical area exceeds a threshold percentage, wherein the outputindicates that the one or more of the channels of the unlicensedspectrum are in the band and can be used for carrier aggregation in theband during the LAA transmissions.
 16. The one or more non-transitorycomputer-readable media of claim 15, wherein the output data includes aninstruction to one or more base stations of a telecommunication networkproximate to the geographical area that permits the one or more basestations to use one or more of the channels of the unlicensed spectrumduring the LAA transmissions with individual ones of the plurality ofUEs.
 17. The one or more non-transitory computer-readable media of claim15, wherein the output data includes at least one of a heat map thatplots the average channel utilization values associated with the one ormore channels over the geographical area, a first chart that indicatesthe average channel utilization values for the individual ones of thechannels within the geographical area, or a second chart that indicatesportions of the geographical area that correspond to common ones of theaverage channel utilization values associated with the one or morechannels.